215 citations · 382 across the 20 of their papers we have counts for
22 papers
IQuest-Q1: Advancing Foundation Capabilities for Agentic CLI Systems
A. Jian Yang, An Huang, Bo Dan +173
We present IQuest-Q1, a sparse Mixture-of-Experts (MoE) agentic foundation model with 320B total parameters (15B activated). IQuest-Q1 is developed through a three-stage process: (…
Multimodal Unlearning Across Vision, Language, Video, and Audio: Survey of Methods, Datasets, and Benchmarks
Nobin Sarwar, Shubhashis Roy Dipta, Zheyuan Liu +1
With the growing adoption of VLMs, DMs, LLMs, and AFMs, these multimodal foundation models can inadvertently encode sensitive, copyrighted, biased, or unsafe cross-modal associatio…
OpenD: A Benchmark for Language-Driven Door and Drawer Opening
Yizhou Zhao, Qiaozi Gao, Liang Qiu +2
We introduce OPEND, a benchmark for learning how to use a hand to open cabinet doors or drawers in a photo-realistic and physics-reliable simulation environment driven by language…
A Survey of Deep Learning for Mathematical Reasoning
Pan Lu, Liang Qiu, Wenhao Yu +2
Mathematical reasoning is a fundamental aspect of human intelligence and is applicable in various fields, including science, engineering, finance, and everyday life. The developmen…
Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering
Pan Lu, Swaroop Mishra, Tony Xia +6
When answering a question, humans utilize the information available across different modalities to synthesize a consistent and complete chain of thought (CoT). This process is norm…
Dynamic Prompt Learning via Policy Gradient for Semi-structured Mathematical Reasoning
Pan Lu, Liang Qiu, Kai-Wei Chang +5
Mathematical reasoning, a core ability of human intelligence, presents unique challenges for machines in abstract thinking and logical reasoning. Recent large pre-trained language…
Structure Extraction in Task-Oriented Dialogues with Slot Clustering
Liang Qiu, Chien-Sheng Wu, Wenhao Liu +1
Extracting structure information from dialogue data can help us better understand user and system behaviors. In task-oriented dialogues, dialogue structure has often been considere…
Triangular Character Animation Sampling with Motion, Emotion, and Relation
Yizhou Zhao, Liang Qiu, Wensi Ai +2
Dramatic progress has been made in animating individual characters. However, we still lack automatic control over activities between characters, especially those involving interact…
ValueNet: A New Dataset for Human Value Driven Dialogue System
Liang Qiu, Yizhou Zhao, Jinchao Li +4
Building a socially intelligent agent involves many challenges, one of which is to teach the agent to speak guided by its value like a human. However, value-driven chatbots are sti…
Learning from the Tangram to Solve Mini Visual Tasks
Yizhou Zhao, Liang Qiu, Pan Lu +3
Current pre-training methods in computer vision focus on natural images in the daily-life context. However, abstract diagrams such as icons and symbols are common and important in…
GenMotion: Data-driven Motion Generators for Real-time Animation Synthesis
Yizhou Zhao, Wensi Ai, Liang Qiu +4
With the recent success of deep learning algorithms, many researchers have focused on generative models for human motion animation. However, the research community lacks a platform…
IconQA: A New Benchmark for Abstract Diagram Understanding and Visual Language Reasoning
Pan Lu, Liang Qiu, Jiaqi Chen +6
Current visual question answering (VQA) tasks mainly consider answering human-annotated questions for natural images. However, aside from natural images, abstract diagrams with sem…
X2Teeth: 3D Teeth Reconstruction from a Single Panoramic Radiograph
Yuan Liang, Weinan Song, Jiawei Yang +3
3D teeth reconstruction from X-ray is important for dental diagnosis and many clinical operations. However, no existing work has explored the reconstruction of teeth for a whole ca…
STAR: Sparse Transformer-based Action Recognition
Feng Shi, Chonghan Lee, Liang Qiu +6
The cognitive system for human action and behavior has evolved into a deep learning regime, and especially the advent of Graph Convolution Networks has transformed the field in rec…
SocAoG: Incremental Graph Parsing for Social Relation Inference in Dialogues
Liang Qiu, Yuan Liang, Yizhou Zhao +5
Inferring social relations from dialogues is vital for building emotionally intelligent robots to interpret human language better and act accordingly. We model the social network a…
Inter-GPS: Interpretable Geometry Problem Solving with Formal Language and Symbolic Reasoning
Pan Lu, Ran Gong, Shibiao Jiang +4
Geometry problem solving has attracted much attention in the NLP community recently. The task is challenging as it requires abstract problem understanding and symbolic reasoning wi…
Towards Socially Intelligent Agents with Mental State Transition and Human Utility
Liang Qiu, Yizhou Zhao, Yuan Liang +4
Building a socially intelligent agent involves many challenges. One of which is to track the agent's mental state transition and teach the agent to make decisions guided by its val…
Atlas-aware ConvNetfor Accurate yet Robust Anatomical Segmentation
Yuan Liang, Weinan Song, Jiawei Yang +3
Convolutional networks (ConvNets) have achieved promising accuracy for various anatomical segmentation tasks. Despite the success, these methods can be sensitive to data appearance…
OralViewer: 3D Demonstration of Dental Surgeries for Patient Education with Oral Cavity Reconstruction from a 2D Panoramic X-ray
Yuan Liang, Liang Qiu, Tiancheng Lu +8
Patient's understanding on forthcoming dental surgeries is required by patient-centered care and helps reduce fear and anxiety. Due to the gap of expertise between patients and den…
Vertical-Horizontal Structured Attention for Generating Music with Chords
Yizhou Zhao, Liang Qiu, Wensi Ai +2
In this paper, we propose a lightweight music-generating model based on variational autoencoder (VAE) with structured attention. Generating music is different from generating text…
Structured Attention for Unsupervised Dialogue Structure Induction
Liang Qiu, Yizhou Zhao, Weiyan Shi +5
Inducing a meaningful structural representation from one or a set of dialogues is a crucial but challenging task in computational linguistics. Advancement made in this area is crit…
Recurrent Neural Networks with Pre-trained Language Model Embedding for Slot Filling Task
Liang Qiu, Yuanyi Ding, Lei He
In recent years, Recurrent Neural Networks (RNNs) based models have been applied to the Slot Filling problem of Spoken Language Understanding and achieved the state-of-the-art perf…